Magnitude of perceived change in natural images may be linearly proportional to differences in neuronal firing rates

David J. Tolhurst*, Michelle P.S. To, Mazviita Chirimuuta, Tom Troscianko, Pei Ying Chua, P. George Lovell

*Corresponding author for this work

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

We are studying how people perceive naturalistic suprathreshold changes in the colour, size, shape or location of items in images of natural scenes, using magnitude estimation ratings to characterise the sizes of the perceived changes in coloured photographs. We have implemented a computational model that tries to explain observers' ratings of these naturalistic differences between image pairs. We model the action-potential firing rates of millions of neurons, having linear and non-linear summation behaviour closely modelled on real V1 neurons. The numerical parameters of the model's sigmoidal transducer function are set by optimising the same model to experiments on contrast discrimination (contrast 'dippers') on monochrome photographs of natural scenes. The model, optimised on a stimulus-intensity domain in an experiment reminiscent of the Weber-Fechner relation, then produces tolerable predictions of the ratings for most kinds of naturalistic image change. Importantly, rating rises roughly linearly with the model's numerical output, which represents differences in neuronal firing rate in response to the two images under comparison; this implies that rating is proportional to the neuronal response.

Original languageEnglish
Pages (from-to)349-372
Number of pages24
JournalSeeing and Perceiving
Volume23
Issue number4
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes

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